Author

Andre L. Moreira

NYU Langone HealthORCID 0000-0002-4922-7295Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Alberto RomagnoniiD· 1 shared Alexandra HardyiD· 1 shared Aurélie SwalduziD· 1 shared Benoît SchmauchiD· 1 shared Brooke E. HowittiD· 1 shared Caroline TruntzeriD· 1 shared Charles MaussioniD· 1 shared Elodie Pronier· 1 shared

Activity by Year

2024-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Alberto RomagnoniORCID

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1 paper

Recent·Most cited

Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients.

Benoît Schmauch, Vincent Cabeli, Omar Darwiche Domingues, Jean-Eudes Le Douget, Alexandra Hardy, Reda Belbahri, Charles Maussion, Alberto Romagnoni, Markus Eckstein, Florian Siegfried Fuchs, Aurélie Swalduz, Sylvie Lantuéjoul, Hugo Crochet, François Ghiringhelli, Valentin Dérangère, , Matteo Cesaroni

This study uses deep learning to predict YAP1/TEAD activity from histology slides, linking histological patterns to disease aggressiveness in cancer patients.

iScience · Dec 20, 2024Peer-reviewedBioinformatics